收藏切换
Prediction of chub mackerel fishing ground distribution in the East China Sea and Yellow Sea based on maximum entropy model and habitat suitability index model
收藏切换
PDF
Ruixing Cao1, Wenjiang Guan1, 2, Feng Gao1, 3, *, Weiwei He1
Haiyang Xuebao | 2023, 45(9) : 72 - 81
Less
收藏切换
Haiyang Xuebao | 2023, 45(9): 72-81
Article
Prediction of chub mackerel fishing ground distribution in the East China Sea and Yellow Sea based on maximum entropy model and habitat suitability index model
Full
Ruixing Cao1, Wenjiang Guan1, 2, Feng Gao1, 3, *, Weiwei He1
Affiliations
  • 1College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China
  • 2The Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai 201306, China
  • 3National Distant-water Fisheries Engineering Research Center, Shanghai Ocean University, Shanghai 201306, China
Published: 2023-09-30 doi: 10.12284/hyxb2023136
Outline
收藏切换

The maximum entropy model (Maxent) and habitat suitability index (HSI) model are widely used in fishery forecasting studies. To compare the forecasting performance of these two models on fishing grounds and improve the scientific management of chub mackerel (Scomber japonicus) resources, this study used the fishery data of chub mackerel in the East China Sea and Yellow Sea from 2003 to 2012, and marine environmental data, including sea surface temperature, sea surface height, sea surface salinity and sea surface temperature gradient, to construct the Maxent model and HSI model. The aim was to analyze and compare the effectiveness of these two models in predicting the habitat of chub mackerel in the East China Sea and Yellow Sea. The quantitative evaluation of the prediction performance of the two models was conducted using the area under curve (AUC) of the receiver operating characteristic (ROC), and the correspondence between the probability of fishing grounds predicted by the models and the percentage of the actual catches. The results showed that: (1) locations predicted by the maximum entropy model to have a high probability of fishing occurrence coincided with actual fishing locations. The probability of predicting fishery occurrence in the sea area without historical fishing data was lower. Locations predicted to have a high habitat index by the HSI model partially overlapped with actual fishing locations. A high habitat index was obtained in the sea area without historical fishing data. The probability of the HSI model predicting non-fishing grounds as fishing grounds was higher than that of the Maxent model; (2) the monthly average AUC values of the Maxent and HSI model were 0.95 and 0.66, respectively, indicating that the Maxent had relatively better predictive results; (3) when using the HSI model, non-fishing grounds data should be added to the model, and the collection of such data should be strengthened otherwise, there is a possibility of overestimation when such models forecast fishing grounds. When using the Maxent, the spatial coverage of fishery data must be improved otherwise, it cannot fully reflect the spatial and temporal distribution dynamics of the fishery. The results of this study provide a reference for improving the accuracy of forecasting for the chub mackerel fishery in the East China Sea and Yellow Sea.

maximum entropy model  /  habitat suitability index model  /  model comparison  /  chub mackerel
Ruixing Cao, Wenjiang Guan, Feng Gao, Weiwei He. Prediction of chub mackerel fishing ground distribution in the East China Sea and Yellow Sea based on maximum entropy model and habitat suitability index model[J]. Haiyang Xuebao, 2023 , 45 (9) : 72 -81 . DOI: 10.12284/hyxb2023136
Year 2023 volume 45 Issue 9
PDF
178
73
Cite this Article
BibTeX
Article Info
doi: 10.12284/hyxb2023136
  • Receive Date:2023-03-22
  • Online Date:2025-12-28
  • Published:2023-09-30
Article Data
Affiliations
History
  • Received:2023-03-22
  • Revised:2023-06-26
Funding
Affiliations
    1College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China
    2The Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai 201306, China
    3National Distant-water Fisheries Engineering Research Center, Shanghai Ocean University, Shanghai 201306, China
References
Share
https://castjournals.cast.org.cn/joweb/hyxb/EN/10.12284/hyxb2023136
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT